Own the performance of large language models in production — the latency, the throughput, the cost-per-token. This is deep inference-optimization work: profiling and tuning at the GPU and serving-engine level to make models run faster and cheaper at scale. You'll join a small, senior team at an established enterprise software company building LLM-powered capabilities into its products.

What you'll do:

• Optimize LLM inference for latency, throughput, and cost — at the kernel and serving-engine level
• Profile and tune GPU performance (CUDA, TensorRT-LLM); apply quantization, speculative decoding, and batching strategies
• Get the most out of serving frameworks like vLLM, SGLang, and Triton — and extend them where they fall short
• Optimize across hardware targets where relevant (NVIDIA and other accelerators)
• Partner with model and platform teams to take new architectures from works to fast